Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA.
J Psychiatr Res. 2021 Jun;138:413-419. doi: 10.1016/j.jpsychires.2021.04.023. Epub 2021 Apr 29.
Depression is characterized by the heterogeneity in anti-depressant treatment response and clinical outcomes. Cognitive impairment may be one of the more practically important aspects of depression. A new approach was to identify neuropsychologically derived depression subtypes based on the trajectory of neuro-cognition such as intelligence quotient (IQ) change. We used a classical premorbid IQ prediction algorithm and then compared predicted premorbid IQ with current IQ. IQ change was used to delineate the patterns of neuropsychological heterogeneity within a large dataset consisting of 131 patients with major depressive disorder (MDD) and 165 healthy controls (HCs). Neurocognitive results from CANTAB and 3 T resting-state fMRI data were compared among the subgroups identified. IQ change heterogeneity identified two subgroups within the MDD group: preserved IQ (PIQ) and deteriorated IQ (DIQ) in MDD. The DIQ subgroup was marked by poorer functioning across multiple cognition domains, including increased impairments in motor speed, cognitive flexibility, and catastrophic thinking when compared to PIQ and HCs. Moreover, cognitive performance of patients with DIQ was correlated with IQ decline. Also, increased brain activity of anterior cingulate cortex and medial prefrontal cortex was found in DIQ but not in PIQ and HCs. IQ-based subgroups of depression may be differentially associated with the extent of neurocognitive impairment and brain activities, which suggests that classifying the cognitive heterogeneity associated with depression may provide a platform to better characterize the neurobiological underpinnings of the disease.
抑郁症的抗抑郁治疗反应和临床结局存在异质性。认知障碍可能是抑郁症更实际重要的方面之一。一种新的方法是基于神经认知轨迹(如智商变化)来确定神经心理学衍生的抑郁症亚型。我们使用了经典的病前智商预测算法,然后将预测的病前智商与当前智商进行比较。智商变化用于描绘由 131 名重性抑郁症 (MDD) 患者和 165 名健康对照 (HC) 组成的大型数据集内的神经心理学异质性模式。对 CANTAB 和 3T 静息状态 fMRI 数据的神经认知结果进行了比较。在 MDD 组内,智商变化的异质性确定了两个亚组:MDD 中的保留智商 (PIQ) 和智商下降 (DIQ)。与 PIQ 和 HCs 相比,DIQ 亚组在多个认知领域的功能较差,包括运动速度、认知灵活性和灾难性思维的损伤增加。此外,DIQ 患者的认知表现与智商下降相关。还发现,DIQ 中前扣带回皮质和内侧前额叶皮质的大脑活动增加,但 PIQ 和 HCs 中没有。基于智商的抑郁症亚组可能与神经认知损伤的程度和大脑活动有不同的关联,这表明对与抑郁症相关的认知异质性进行分类可能为更好地描述疾病的神经生物学基础提供一个平台。